Acceler8 Talent

About the Company

Acceler8 connects the top AI companies with the talent to scale fast, reach milestones, and secure funding so you can launch your AI products with confidence. We're at the forefront of connecting exceptional talent with ground breaking opportunities. We operate as the driving force behind visionary AI startups, actively shaping the future of technology across the Bay Area, Boston, New York, and beyond. Our expertise spans a diverse array of tech specialties, including ML Research & Engineering, Software for ML Platforms, Semiconductor & Chip Design, Silicon Photonics, High Performance Computing, and Machine Learning Compilers. We serve as the catalyst for talent, ensuring that our clients have access to the most qualified professionals to propel their innovations forward. We'll build the team that turns your vision into reality. Are you ready to Acceler8?Contact us today! https://www.acceler8talent.com/contact-us/ _____________________________________________ Important Notice: Scam Alert Targeting Job Seekers We want to inform our network about a scam that is currently targeting job seekers through platforms like WhatsApp and LinkedIn. Please be aware that these messages are not from us or any of our employees. Rest assured, we are actively monitoring this situation and are taking it very seriously. If you have any doubts or concerns, please contact us directly through our official website https://www.acceler8talent.com/ or email us at info@acceler8talent.com. Please do not submit any personal information via links that are not from our official website.

Listed Jobs

Company Name

Acceler8 Talent

Job Title

Machine Learning Researcher (LLMs)

Job Description

Job title: Machine Learning Researcher (LLMs) Role Summary: Develop and scale large language model solutions for scientific discovery, creating end‑to‑end pipelines from prototype to production with rigorous, domain‑aware evaluation and close collaboration with multidisciplinary teams. Expectations: - Convert early prototypes into production‑grade systems that enhance scientific workflows. - Design, execute, and interpret extensive experiments and benchmarks. - Communicate findings and requirements effectively to scientists, engineers, and stakeholders. - Maintain a curiosity‑driven, data‑driven mindset with a focus on clear, reproducible research. Key Responsibilities: 1. Design and prototype LLM reasoning, planning, and tool‑use workflows tailored to biological, chemical, and materials science problems. 2. Build custom evaluation frameworks incorporating domain expertise; benchmark models against rigorous metrics. 3. Scale prototypes into scalable, production‑ready systems, integrating continuous feedback loops with research and engineering teams. 4. Lead systematic experimentation, including ablations, hyper‑parameter sweeps, and performance analyses. 5. Translate scientific needs into concrete technical specifications and guide multidisciplinary collaboration. Required Skills: - Deep knowledge of large‑language model architectures, fine‑tuning techniques, and reinforcement learning from human feedback. - Strong research background in machine learning, algorithm development, and statistical evaluation. - Experience deploying distributed training, inference serving, and monitoring for large models. - Proficiency in Python, PyTorch/TensorFlow, and version control/Git workflows. - Ability to design domain‑specific benchmarks and interpret complex results. - Excellent communication skills for writing reports and presenting to scientific audiences. Required Education & Certifications: - Ph.D. or M.S. in Computer Science, Machine Learning, Artificial Intelligence, or a closely related field; equivalent professional experience may be considered. - No mandatory certifications, but familiarity with cloud ML platforms (AWS, GCP, Azure) is advantageous.

Cambridge, United states

On site

08-12-2025

Company Name

Acceler8 Talent

Job Title

Machine Learning Engineer

Job Description

**Job title**: Machine Learning Engineer **Role Summary**: Lead the full lifecycle of machine learning solutions, from concept to production. Design, develop, deploy, and continuously optimize scalable AI models that support high‑performance systems. Work closely with software and systems teams to ensure models are reliable, maintainable, and aligned with product objectives. **Expectations**: - Translate business requirements into technical ML strategies. - Build end‑to‑end AI pipelines that can handle massive workloads with low latency. - Maintain model quality through rigorous monitoring, testing, and iterative improvement. - Collaborate across engineering disciplines to embed ML capabilities into production environments. **Key Responsibilities**: - Develop, train, and fine‑tune ML models using modern frameworks (e.g., PyTorch, TensorFlow). - Deploy models to scalable infrastructure (Docker, Kubernetes, cloud services). - Design and implement monitoring, logging, and alerting for model performance and drift. - Optimize model inference for speed, memory, and cost efficiency. - Integrate models into product workflows and APIs. - Participate in code reviews, architecture discussions, and continuous integration pipelines. **Required Skills**: - Strong programming proficiency in Python; experience with ML libraries (scikit‑learn, PyTorch, TensorFlow, Keras). - Familiarity with model serving frameworks (ONNX, TensorRT, TensorFlow Serving). - Knowledge of containerization (Docker) and orchestration (Kubernetes). - Experience with cloud AI services (AWS AI/ML, GCP AI Platform, Azure ML) or on‑prem deployment. - Ability to design and maintain data pipelines (ETL, stream processing). - Solid understanding of data engineering principles, feature engineering, and model evaluation metrics. - Excellent problem‑solving, communication, and collaboration skills. **Required Education & Certifications**: - Bachelor’s (or higher) degree in Computer Science, Electrical Engineering, Data Science, or related field. - Proven professional experience (≥3 years) in machine learning or AI engineering. - Certifications in cloud AI/ML platforms or relevant technologies are a plus.

Cambridge, United states

On site

08-12-2025

Company Name

Acceler8 Talent

Job Title

Distributed Systems Engineer

Job Description

**Job title:** Distributed Systems Engineer **Role Summary:** Design, build, and operate high-performance distributed data, coordination, and storage systems that support ultra-long‑context AI model training and inference across GPU clusters, ensuring fault tolerance, high availability, and scalability on public cloud platforms. **Expectations:** - Deliver end‑to‑end distributed solutions for large‑scale GPU workloads. - Achieve robust fault detection, automated recovery, and sustained high availability. - Troubleshoot cross‑stack issues involving GPUs, networking, storage, OS, and cloud infra. **Key Responsibilities:** - Architect and implement distributed data and coordination frameworks for ultra‑long‑context model training and inference. - Develop high‑throughput, durable storage and caching layers tailored to GPU infrastructure. - Dive into deep learning framework internals to optimize performance in highly distributed settings. - Build automation tools for monitoring, fault detection, recovery, and scaling across GPU clusters. - Diagnose and resolve complex stack‑wide problems spanning hardware, software, and cloud services. **Required Skills:** - Deep expertise in distributed systems design and operation on public cloud platforms (AWS, GCP, Azure). - Proven experience with highly available, high‑throughput data pipelines and storage. - Strong knowledge of distributed databases, batch or stream processing engines, or distributed file systems. - Hands‑on skill set in GPU hardware, networking, Linux/Unix, and container orchestration (Kubernetes, Docker). - Excellent problem‑solving across the systems stack, with the ability to learn quickly in a frontier environment. **Required Education & Certifications:** - Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, or related field. - Relevant certifications (e.g., AWS Certified Solutions Architect, GCP Professional Cloud Architect) preferred but not mandatory.

San francisco, United states

On site

23-12-2025

Company Name

Acceler8 Talent

Job Title

Research Scientist (Gen AI)

Job Description

**Job Title** Research Scientist (Gen AI) **Role Summary** Lead research on large‑language‑model (LLM) powered autonomous agents that reason, plan, and interact with the physical world. Develop reasoning and planning frameworks, structured tool‑use and memory systems, and safe policies for long‑horizon decision‑making. Train and evaluate models on real engineering and scientific tasks in collaboration with systems, simulation, and infrastructure teams. **Expectations** - Design and iterate innovative LLM‑based agent architectures that demonstrate measurable long‑term reasoning, structured tool use, and safety. - Deliver rigorous research results, publish in top ML/AI venues, and convert research concepts into production‑ready models. - Drive cross‑functional integration, meet tight milestones, and maintain high standards of experiment reproducibility. - Communicate findings clearly to both technical and non‑technical audiences. **Key Responsibilities** - Build and refine LLM reasoning, planning, and tool‑use pipelines. - Implement structured memory, reflection, and multi‑step workflow mechanisms. - Design, train, and evaluate supervised fine‑tuning (SFT), RLHF, DPO, verifier‑guided RL, and other policy‑training methods. - Benchmark model performance on real‑world engineering/science scenarios. - Collaborate with systems, simulation, and infra experts to deploy models in autonomous systems. - Present research progress at internal workshops and external conferences. **Required Skills** - Deep research background in LLMs, reasoning, or autonomous agents. - Expertise with SFT, RLHF/DPO, verifier‑guided RL, and related training pipelines. - Demonstrated ability to design and evaluate long‑horizon behaviors. - Proficiency in Python, PyTorch/TensorFlow, and large‑scale model training. - Strong analytical, problem‑solving, and communication skills. - Comfortable working in a fast‑paced, interdisciplinary R&D environment. **Required Education & Certifications** - Ph.D. or M.S. in Computer Science, Machine Learning, Artificial Intelligence, Robotics, or a closely related field. - Proven publication record in leading ML/AI conferences (NeurIPS, ICML, ICLR, ICRA, etc.) preferred. - Background in safety and robustness of autonomous systems is advantageous.

San francisco bay, United states

On site

26-01-2026